Enterprise Evidence Repository
A controller is configured to generate and propagate instructions to an execution agent which, in turn, is configured to collect and deposit collected artifacts into a repository. Write access to a location in the repository for collected artifacts that are to be deposited into a specified location is granted to the execution agent. Once the execution agent deposits the collected artifacts in the specified location in the repository, a summary of collected artifacts is propagated to the controller. The controller manages appropriate levels of access to the collected artifacts, while the repository enforces the level of access. The controller can grant read only access to the collected artifacts or it can allow for controlled changes to be made to the metadata associated with the collected artifact. An agent processes the data and generates additional metadata that can be associated with the collected artifacts and then saved in the repository. A system can have more than one repository, where the controller allocates storage in an appropriate repository and issues instructions to the execution agent with the location in an appropriate repository. The summary of the actual collections is then propagated to the controller from the repositories.
1. Technical Field
The invention relates to electronic discovery (eDiscovery). More particularly, the invention relates to an enterprise evidence repository.
2. Description of the Prior Art
Electronic discovery, also referred to as e-discovery or eDiscovery, concerns discovery in civil litigation, as well as tax, government investigation, and criminal proceedings, which deals with information in electronic form. In this context, the electronic form is the representation of information as binary numbers. Electronic information is different from paper information because of its intangible form, volume, transience, and persistence. Also, electronic information is usually accompanied by metadata, which is rarely present in paper information. Electronic discovery poses new challenges and opportunities for attorneys, their clients, technical advisors, and the courts, as electronic information is collected, reviewed, and produced. Electronic discovery is the subject of amendments to the Federal Rules of Civil Procedure which are effective Dec. 1, 2006. In particular, for example, but not by way of limitation, Rules 16 and 26 are of interest to electronic discovery.
Examples of the types of data included in e-discovery include e-mail, instant messaging chats, Microsoft Office files, accounting databases, CAD/CAM files, Web sites, and any other electronically-stored information which could be relevant evidence in a law suit. Also included in e-discovery is raw data which forensic investigators can review for hidden evidence. The original file format is known as the native format. Litigators may review material from e-discovery in any one or more of several formats, for example, printed paper, native file, or as TIFF images.
The revisions to the Federal Rules formally address e-discovery and in the process, have made it a nearly certain element of litigation. For corporations, the rules place a very early focus on existing retention practices and the preservation and discovery of information.
In response to the climate change in the e-discovery arena, corporations are:
1) enhancing their processes for issuing legal holds and tracking collections;
2) looking for ways to reduce the costs of collecting, processing and reviewing electronic data; and
3) looking upstream to reduce the volume of unneeded data through better retention policies that are routinely enforced.
The new field of e-discovery management has emerged to assist companies that are overwhelmed by the requirements imposed by the new rules and the spate of legal and regulatory activity regarding e-discovery.
Currently, e-discovery management applications (EMA) rely on a variety of approaches to store electronic data for e-discovery. For example:
EMAs store content as binary objects in a database. Transaction information as well as file collections are typically stored in the same relational database located on a database server;
EMAs also store content as content objects in a content management system. EMAs can use a content management system, such as EMC DOCUMENTUM, EMC CORPORATION, Hopkinton, Mass., to store unstructured content; and
EMAs can use a local or networked file system to store content as files in a file system and a database to store file metadata.
Such conventional methods provide convenience and functionality, such as allowing the data to be updated, allowing it to be checked in and checked out, and so on. However, data stored for the purpose of e-discovery typically has the character of being immutable and unstructured, i.e. the data is to be permanently stored, or at least stored for a very long time; the data is not to be changed or updated or checked-in or -out very often; and it is typically unnecessary to organize or structure the data in a database or content base. In view of the immutable, unstructured nature of e-discovery data, such conventional storage approaches, in spite of their convenience and functionality, involve a number of disadvantages:
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- High hardware cost: Databases, content management systems, and local file systems are usually stored in arrays of hard disks. The high hardware expense may be justified for transactional data, but it is exorbitant in the case of the immutable, unstructured content typically used in e-discovery;
- High maintenance cost: In all of the above scenarios, maintenance requires a skilled administrator. In the case of a database, the administrator must be trained in database technology; in case of a content management system (which usually resides on top of a database), the administrator must also be skilled in content management systems. These maintenance costs may amount to hundreds of thousands of dollars in salary and thousands in training costs. As above, such expense may be justified for transactional data but is needless in the case immutable unstructured content;
- Extra information technology (IT) planning and coordination: Necessary disk space must be projected and purchased upfront, requiring close involvement of IT personnel, e.g. coordination between parties such as the Chief Legal Officer and the Chief Information Officer;
- High capital investment: To ensure available disk space, the company has to buy more disk space than it needs at any particular time; and
- Inefficiencies in cost accounting: It would be beneficial to treat storage as a cost related to a particular litigation matter as opposed to a capital expense.
Thus, there exists a need to provide a way of storing collected content in e-discovery applications that eliminates unnecessary expense and managerial and administrative overhead, thus achieving cost savings and simplifying operations.
SUMMARY OF THE INVENTIONAn embodiment of the invention comprises a system that includes a controller that is configured to generate and propagate instructions to an execution agent. The execution agent is configured to collect and deposit collected artifacts into a repository. The controller coordinates allocation of the storage in the repository. The controller propagates the collection instructions to the execution agent: the instructions contain a location for depositing collected artifacts. Write access must be granted to the execution agent. Such access is provided to a location in the repository for collected artifacts that are to be deposited into a specified location. Once the execution agent deposits the collected artifacts in the specified location in the repository, a summary of collected artifacts is propagated to the controller, thus providing transparency into the overall collection process.
Collected artifacts can be made available to a processing agent that is configured to perform various processing functions on them. The controller manages appropriate levels of access to the collected artifacts, while the repository enforces the level of access. The controller can grant read only access to the collected artifacts or it can allow for controlled changes to be made to the metadata associated with the collected artifact. An agent can process the data and generate additional metadata that can be associated with the collected artifacts and then saved in the repository.
Collected artifacts, along with the contextual data and additional metadata, reside in the repository. The controller can grant read only access to an agent that is capable of extracting all of the data from the repository and exporting it out.
A system can have more than one repository to store collected artifacts and metadata. In such a configuration, the controller allocates storage in an appropriate repository. The controller issues instructions to the execution agent with the location in an appropriate repository. The summary of the actual collections is then propagated to the controller from the repositories.
The following documents are cited herein to provide background information in connection with various embodiments of the herein disclosed invention. These documents are incorporated herein in their entirety based upon this reference thereto:
Discovery Cost Forecasting Patent Applications:Forecasting Discovery Costs Using Historic Data; Ser. No. 12/165,018; filed 30 Jun. 2008; attorney docket no. PSYS0007;
Forecasting Discovery Costs Based On Interpolation Of Historic Event Patterns; Ser. No. 12/242,478; filed 30 Sep. 2008; attorney docket no. PSYS0012;
Forecasting Discovery Costs Based on Complex and Incomplete Facts; Ser. No. 12/553,055; filed 2 Sep. 2009; attorney docket no. PSYS0013; and
Forecasting Discovery Costs Based On Complex And Incomplete Facts; Ser. No. 12/553,068; filed 2 Sep. 2009; attorney docket no. PSYS0015;
Automation Patent Application:Method And Apparatus For Electronic Data Discovery; Ser. No. 11/963,383; filed 21 Dec. 2007; attorney docket no. PSYS0001; and
Collection Transparency Patent Application:Providing Collection Transparency Information To An End User To Achieve A Guaranteed Quality Document Search And Production In Electronic Data Discovery; Ser. No. 12/017,236; 21 Jan. 2008; attorney docket no. PSYS0003.
TerminologyThe following terms have the meaning associated with them below for purposes of the discussion herein:
Enterprise Discovery Management System (EDMS): technology to manage eDiscovery workflow in an enterprise such as the Atlas Enterprise Discovery Management system offered by PSS Systems of Mountain View, Calif.;
Enterprise Content Management (ECM) tools: a set of technologies to capture, manage, retain, search, and produce enterprise content, such as IBM's FileNet;
Early Case Assessment (ECA) tools: technology to evaluate risks associated with eDiscovery by identifying and analyzing relevant evidence;
Discovery Cost Forecasting (DCF): technology to model, forecast costs associated with eDiscovery, such as the Atlas DCF;
Evidence Repository (EvR): a system and processes for securely collecting, preserving, and providing access to documents and related metadata collected as part of eDiscovery;
Collection Manifest: a file describing various attributes of the contents of a collection including, but not limited to, the following type of metadata: chain of custody, file types, sizes, MAC dates, original locations, etc; and
Self-collections: a process of collection in which a legal function sends collection instructions directly to custodians and the custodians perform collection from local PCs, email, PDAs, file share, etc.
Abstract SystemCollected artifacts can be made available to a processing agent (see 510 on
Collected artifacts, along with the contextual data and additional metadata, reside in the repository. The controller can grant read only access to an agent that is capable of extracting all of the data from the repository and exporting it out.
A system can have more than one repository to store collected artifacts and metadata (see
eDiscovery System
The EDMS propagates the legal case and other process data and metadata to the evidence repository, including (see
The EDMS 210 also generates a structured collection plan with detailed collection instructions. The IT 220 receives the instructions and performs collections from the data source 230, depositing the collected documents to the location of the directory in the staging area specified in the collection instructions received from EDMS.
Content source metadata is propagated along with the content of the collected documents. This type of metadata is derived from the content of collected file, for example size in bytes, page count, checksum, or hash code, calculated based on the content of a file, MIME type, etc.
Location metadata is propagated along with the contents of collected files. This type of metadata represents the location from where the files were originally collected. Examples of the metadata include: name or address of a PC, server, file path, file name, and modified, accessed, and created date of the file.
Collected documents and the metadata are ingested from the staging area to the evidence repository. Collected documents are grouped and linked to appropriate metadata that has been previously propagated to the evidence repository.
Collection Staging AreaWhen a new collection plan is created and published, the EDMS automatically propagates the collection plan, custodians, and data source information, and creates a directory structure in the collection staging area, which in
The EDMS also propagates the access control rules to the staging area by granting an appropriate level of access on a target collection deposit directory to an appropriate user or a group of users, based on the work assignment as defined in the EDMS.
Having an automatically managed staging area for collections enables simple and reliable collection process. The EDMS contains all of the data necessary to execute a collection based on the collection parameters specified by the legal department as part of the collection plan. Folders in the staging area are automatically provisioned for collections, data sources, and custodians. IT does not need to create folders manually. Collection instructions are automatically issued by the EDMS when the collection plan is published. The drop-off location parameters are automatically generated based on the network file share location path of an auto-provisioned directory in the collection staging area.
Evidence RepositoryThe evidence repository manages large volumes of collected documents and metadata and can be built on top of an existing content management system, such as an ECM.
The legal case entity is a container for the collection or interview plans 440, 441, 442, 443 which can be further categorized into structured collection plans, such as 440, 442, 443, and self collection plans 441. Collection plans have process metadata propagated from the EDMS that includes, for example, the following properties: name, status, date, collection parameters, etc.
Collection plans contain collection logs 460, 461, 462, 463, 464, 465. Collection logs have process metadata that includes, for example custodian, data source, log entry, conducted by, date conducted, status, etc. The collection logs contain evidence items that include the content and metadata of the collected documents. The metadata for the collection log is comprised of the process, source, and location metadata, as defined above.
Self-collectionsAdvanced EDMS systems, such as the Atlas LCC, allow for custodian self-collections. This is a type of collection process when individual custodians receive collection instructions from the legal department and collect evidence, such as emails, documents, and other data, with easy to use tools provided to individual custodians. When using that mechanism the content and metadata may be collected to a dedicated EDMS storage.
The EDMS is responsible for propagating the data collected as part of a self-collection to the evidence repository.
Existing collections stored in EDMS are automatically migrated by moving the content and related case metadata to the evidence repository. This allows for centralized evidence management regardless of the type of a collection and its origins.
Data ProcessingData processing is an important part of the overall eDiscovery process. The EDMS can grant an appropriate level of access to users authorized to use a processing tools against the collected data stored in the evidence repository to enable the data processing. Examples of such access include read-only access to the case data and metadata or a subset of this data, and write access to a subset of metadata. Some data processing tools, such as Early Case Assessment (ECA) tools, can generate additional metadata, such as tags, notes, etc. The metadata generated by such a tool can be stored in the evidence repository if the EDMS grants write access on the subset of metadata associated with documents in the context of a specified legal case, plan, etc.
Data ExportExport tools 520 (see
Export metadata is a metadata associated with an event of exporting set of documents for an outside review. The metadata contains, for example, the date of export, volume of export in bytes, estimated number of pages exported, number of documents exported, etc.
DCF MetadataThe evidence repository is expected to track the overwhelming majority of the collected data. Facts created as a result of the collection, processing, and exporting of the collected data are automatically propagated from the evidence repository to a DCF system. Having the most accurate and up-to date facts is critical for reliable and precise eDiscovery cost modeling and forecasting.
The collected content is processed and analyzed by using an ECA 510 or similar set of tools. The collected content is tagged with additional ECA metadata and the metadata is propagated to the evidence repository. The metadata can be further aggregated and propagated to the DCF system and used to improve the accuracy of the discovery cost modeling and forecasting further.
Export tools 520 are used to extract the content and metadata of documents collected in the evidence repository and package and ship the data for an outside review or other use. The volume and timing metrics, such as volume collected in pages and GB, timing of collections, and number of custodians collected from or associated with an export event, are critical for an accurate discovery cost modeling and forecasting. The evidence repository enables highly reliable and repeatable automated process of propagating the export metadata to DCF when it becomes available.
The export data propagated to the DCF includes, for example, volume of export in bytes, estimated page count, date of export, number of documents, etc.
Ingestion ProcessThe ingestion process is responsible for ingesting the documents and metadata deposited into the collection drop-off locations within the staging area to the evidence repository.
The ingestion process relies on relationships between a folder in the staging area and collection log entity in the ECM that were previously established by the EDMS. Based on the location of documents in the staging area, the ingestion process finds previously created corresponding collection log entities in the evidence repository and links documents ingested from a collection log folder to the collection log entity in the evidence repository.
In some cases collections might also include additional metadata in a form of a collection manifest which can be in proprietary formats or in an XML based formats, such as EDRM XML. Collection manifest metadata is ingested along with collected contents. A collection manifest contains additional metadata including, for example, chain of custody, original location, etc. That metadata gets associated with document evidence entity as part of the ingestion process.
Improve ReliabilityThe reliability and accuracy of the collection process can be further improved by adding a secure token to the collection instructions for the IT. The secure token is a file containing information that uniquely identifies the identity of an individual collection target in a context of a collection plan.
The IT is instructed to deposit the token along with the collected files into the drop-off location specified in the instructions. As part of the ingestion process the system automatically validates the integrity of the collection including chain of custody and detects inconsistencies by comparing the information in the secure token against the expected collection target, collection plan, and other attributes based on the location from the where collected data is being ingested Depending on the ingestion policies such as a collection can be rejected. Exceptions are escalated to an appropriate authority for handling. If, upon the ingestion validation, the system detects that IT has mistakenly deposited data collected for a target into incorrect location along with a secure token for a given target, the system rejects the collection and alerts appropriate IT users and, optionally the legal department, with all of the details necessary to correct the situation by placing collected data in an appropriate location. This affects the overall status of the collection process propagated to EDMS, making it transparent to all of the parties involved until the issue is resolved.
Collection and Metadata Re-useThe evidence repository holds large volumes of collected data including, for example, content, source, location, process, export, DCF metadata and the metadata generated by ECA and other data processing tools. Collection with subsequent analysis and culling can be very costly, especially if done repeatedly. Redundant collection can be reduced or eliminated through the collection re-use.
An entire set the evidence metadata or a subset can also be reused taking a full advantage of the analysis, culling, and export that occurred in the legal case and collection plan being reused.
MonitoringThe EDMS 210 is responsible for the overall collection process. All the stages of the overall process report exceptions, a summary, and important statistics back to the EDMS. The EDMS aggregates the monitoring data from all the stages of the collection process, thus providing additional analytics. The EDMS thus enables visibility into the overall collection process.
The staging area 260 is monitored by analyzing the contents of the drop-off collection locations. The following exceptions and statistics, for example, are reported back to the EDMS: number of files deposited, pending ingestion, failed to delete, failed to ingest within the time limit, etc. These statistics are grouped by collection log, collection plan, legal case, and repository.
The evidence repository is monitored using platform specific mechanisms to detect new documents matching appropriate criterions. The following exceptions and statistics, for example, are reposted back to the EDMS: number of files ingested, failed to link to an appropriate collection log, various timeouts, etc. These statistics are grouped by collection log, collection plan, legal case, and repository and are propagated to the EDMS.
The data processing tools 910 may require an additional content indexing or linking steps for the collected data to become available for processing. For example, many ECA tools employ more sophisticated content and metadata indexing mechanism that evidence repository may provide. This requires additional processing as part of making the collected data available for the analysis. The following exceptions and statistics, for example, are reposted back to the EDMS from the data processing step: number of files available for analysis, number of files pending, number of files failed, various timeouts, etc. These statistics are grouped by collection log, collection plan, legal case, and repository and are propagated to the EDMS.
Multiple RepositoriesThe system supports a configuration with multiple repositories. All the repositories have a dedicated staging area from where the collected data is ingested to each individual repository. The EDMS maintains a catalog of evidence repositories which contains the names, access control rules, and path to the root of the staging area for each repository.
The evidence repository can be selected for a matter type, legal case, and collection plan. When a collection plan is published, the EDMS allocates storage and provision directories in the staging area of a selected evidence repository. The EDMS propagates the legal case and other process data and metadata to the appropriate evidence repository.
The EDMS generates and propagates collection instructions to an IT or an automated collection tools such as Atlas ACA containing the location of the staging area for a selected repository.
Many countries have data protection laws designed to protect information considered to be personally identifiable. For example, EU directives establish a level of protection that effectively makes data transfer from an EU member to the US illegal.
A multiple local evidence repositories can be set up to eliminate the need to transfer the data across jurisdictions. The instructions are generated such that collected content and metadata are deposited in a location within the jurisdiction specific staging area. Collection is ingested into a local ECM within the local evidence repository.
Multiple repositories with various levels of security can be used depending on a legal case security group, individual legal case, and collection plan. Thus, a collection plan involving custodians and data sources located in an IT department 121 is propagated to a default repository 1010. For a case with increased level of security the collection instructions are generated in a way that collected content and metadata are deposited and managed by a secure repository.
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- Select DS and associated collection template
- Identify custodians
- Provide collection parameters
- Click on the ‘ownership’ tab and assign the owners—IT personnel
- Publish collection plan, e.g. initial email collection from key players for a specified date range with specified list of keyword
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- Provision directories
- Provision access control, e.g. grant write-only or read-write access to the provisioned directories for appropriate IT users
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- Collection metadata is automatically propagated to an EvR
- Access Control data is propagated to the repository
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- Create a case container
- Propagate collection metadata from repository to the data processing tool
- Propagate access control data from EDMS to the data processing tool
- Set up search and indexing tasks
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- IT person or a group identified as owner of the collection plan on the IT side finds a new collection request/plan in ‘My Tasks’ tab (see
FIG. 11 ) - Instructions contain a list of parameters and list of custodians Collection instructions might define a number of custodians, e.g. John S, Amy B. etc, and list of parameters of various types, e.g. date range, list of keywords, etc. (see FIG. 12)e
- IT person clicks on the a specific custodian, this opens up custodian view (see
FIG. 13 ) - New auto-calculated parameter ‘Evidence Repository Collection Location’ shows location where collected files should be deposited Instructions clearly state that all collected documents are to be placed in the specified directory., e.g. \\server_name\path_element1\path_element2\deposit_directory
- Clicking on the new parameter opens Windows Explorer, pointing to an automatically provisioned location to allow IT personnel to deposit collected files at that location for a given custodian, collection plan, etc
- Secure token is optionally provided as part of the collection instructions
- IT person or a group identified as owner of the collection plan on the IT side finds a new collection request/plan in ‘My Tasks’ tab (see
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- Use existing collection process and tools
- Optional secure token is deposited into the specified location
- Collection for a given custodian deposited in the specified location
- Upon finishing collection IT personnel set status for a custodian as completed (see
FIG. 14 )
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- Files are processed as soon as deposited into the designated directory
- Additional validation performed to ensure that the files were deposited into correct directory using secure token validation
- All the documents collected for a given matter are automatically propagated to a data processing tool via automated search and import functionality of the processing tools or external timer task.
- Data on the collection summary is propagated to the DCF
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- Legal user selects a legal case
- Select an evidence repository within the case
- User is taken to a data processing or ECA tool, such as the IBM eDiscovery analyzer
Access control is propagated from EDMS so only authorized users get access to the case data
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- Custom search template exposes EDMS specific metadata, such as matterId, requested, collection log, etc.
- User or a group of users performs analysis, culling etc. using eDA
- Data on the data analysis summary is propagated to the DCF
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- Authorized legal user creates a set of data to be exported for outside review
- Data on the export summary is propagated to the DCF
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- Collection deposit process: How many files deposited, processed
- Collection ingestion process: How many files ingested, pre-processed (archives expanded, prepared for indexing), metadata associated, errors, etc
- Analysis preparation: How many files were prepared for analysis, indexed, added to a case, errors
The computer system 1600 includes a processor 1602, a main memory 1604 and a static memory 1606, which communicate with each other via a bus 1608. The computer system 1600 may further include a display unit 1610, for example, a liquid crystal display (LCD) or a cathode ray tube (CRT). The computer system 1600 also includes an alphanumeric input device 1612, for example, a keyboard; a cursor control device 1614, for example, a mouse; a disk drive unit 1616, a signal generation device 1618, for example, a speaker, and a network interface device 1628.
The disk drive unit 1616 includes a machine-readable medium 1624 on which is stored a set of executable instructions, i.e. software, 1626 embodying any one, or all, of the methodologies described herein below. The software 1626 is also shown to reside, completely or at least partially, within the main memory 1604 and/or within the processor 1602. The software 1626 may further be transmitted or received over a network 1630 by means of a network interface device 1628.
In contrast to the system 1600 discussed above, a different embodiment uses logic circuitry instead of computer-executed instructions to implement processing entities. Depending upon the particular requirements of the application in the areas of speed, expense, tooling costs, and the like, this logic may be implemented by constructing an application-specific integrated circuit (ASIC) having thousands of tiny integrated transistors. Such an ASIC may be implemented with complementary metal oxide semiconductor (CMOS), transistor-transistor logic (TTL), very large systems integration (VLSI), or another suitable construction. Other alternatives include a digital signal processing chip (DSP), discrete circuitry (such as resistors, capacitors, diodes, inductors, and transistors), field programmable gate array (FPGA), programmable logic array (PLA), programmable logic device (PLD), and the like.
It is to be understood that embodiments may be used as or to support software programs or software modules executed upon some form of processing core (such as the CPU of a computer) or otherwise implemented or realized upon or within a machine or computer readable medium. A machine-readable medium includes any mechanism for storing or transmitting information in a form readable by a machine, e.g. a computer. For example, a machine readable medium includes read-only memory (ROM); random access memory (RAM); magnetic disk storage media; optical storage media; flash memory devices; electrical, optical, acoustical or other form of propagated signals, for example, carrier waves, infrared signals, digital signals, etc.; or any other type of media suitable for storing or transmitting information.
Although the invention is described herein with reference to the preferred embodiment, one skilled in the art will readily appreciate that other applications may be substituted for those set forth herein without departing from the spirit and scope of the present invention. Accordingly, the invention should only be limited by the Claims included below.
Claims
1. A computer implemented method for storing and accessing collected artifacts in an electronic discovery system (EDMS), comprising the steps of:
- providing an evidence repository for managing collected artifacts along with contextual data and metadata;
- providing a collection agent configured to perform artifact collection and to deposit collected artifacts to said repository; and
- providing an EDMS configured to manage electronic discovery workflow in an enterprise and to issue and propagate instructions to said collection agent.
2. The method of claim 1, wherein said evidence repository further comprises a transient storage area (staging area) to which collected artifacts are deposited.
3. The method of claim 2, wherein said EDMS is configured to control space allocation in said transient storage area for upcoming collections.
4. The method of claim 1, further comprising the step of:
- said evidence repository further providing a content management module configured to provide advanced collaboration capabilities, extensible metadata, and access control.
5. The method of claim 4, further comprising the step of:
- propagating eDiscovery process metadata from said EDMS to said evidence repository.
6. The method of claim 5, said eDiscovery process metadata comprising any of the following data: collection target, reasons for collection, collected by, collected on, collection plan, and legal case.
7. The method of claim 6, said eDiscovery process metadata further comprising external properties.
8. The method of claim 4, wherein said EDMS is configured to manage access control.
9. The method of claim 8, further comprising the step of:
- propagating access control rules from said EDMS to said evidence repository.
10. The method of claim 9, further comprising the step of:
- granting a specific data processing tool read access to a selected subset of said collected artifacts in said evidence repository, as defined by said EDMS.
11. The method of claim 10, said data processing tool comprising an early case assessment (ECA) tool.
12. The method of claim 11, further comprising the step of:
- said data processing tool writing application specific metadata associated with said collected artifacts into said evidence repository.
13. The method of claim 1, further comprising the step of:
- providing a data exporting tool that is granted read access to said collected artifacts in said evidence repository to extract collected artifacts and metadata and to package said extracted collected artifacts and metadata for outside review.
14. The method of claim 13, further comprising the step of:
- extracting a summary of said extracted collected artifacts and metadata, said summary comprising any of the following characteristics of an export: date, purpose, description, volume in MB, estimated number of pages, number of documents overall and broken down by document type and by person or data source.
15. The method of claim 14, further comprising the step of:
- propagating said export metadata from said evidence repository to said EDMS.
16. The method of claim 14, further comprising the step of:
- propagating said export metadata from said evidence repository to a discovery cost forecasting system (DCF).
17. The method of claim 1, further comprising the step of:
- automatically issuing collection instructions for IT and integrating said collection instructions with an overall discovery workflow.
18. The method of claim 17, wherein said instructions comprise any of a unique location of a collection staging area for a given legal case, a collection plan, a collection log, a data source, and a custodian.
19. The method of claim 1, further comprising the step of:
- issuing automated preservation and collection instructions and propagating said instructions to an automated or semi-automated collection tool.
20. The method of claim 17, wherein said collection instructions comprise a secure token for identifying collection parameters, wherein said secure token is configured to automatically validate integrity of a collection, including chain of custody.
21. The method of claim 1, further comprising the step of:
- propagating collected artifacts and metadata for self-collections from said EDMS to said evidence repository.
22. The method of claim 1, further comprising the step of:
- collecting artifacts and metadata for self-collections directly into said evidence repository.
23. The method of claim 1, further comprising the step of:
- migrating existing collections including artifacts and metadata stored in said EDMS into said evidence repository.
24. The method of claim 2, further comprising the step of:
- ingesting collected artifacts from a staging area into said evidence repository.
25. The method of claim 24, further comprising the step of:
- automatically collating collected artifacts and automatically associating metadata that has already been propagated to said evidence repository with said collected artifacts as appropriate.
26. The method of claim 24, further comprising the step of:
- ingesting additional metadata along with collected artifacts from a staging area, said additional metadata comprising any of a chain of custody, document locations, and process metadata for collected artifacts.
27. The method of claim 1, further comprising the step of:
- reusing artifacts collected for a first case in the context of one or more other cases.
28. The method of claim 27, further comprising the step of:
- reusing any of location, process, export, and metadata generated by an early case assessment (ECA) tool and other analytical tools across a plurality of cases.
29. A computer implemented method for storing and accessing collected artifacts in an electronic discovery system (EDMS), comprising the steps of:
- providing a plurality of evidence repositories for managing collected artifacts along with contextual data and metadata;
- providing a collection agent configured to perform artifact collection and to deposit collected artifacts to said repositories; and
- providing an EDMS configured to manage electronic discovery workflow in an enterprise and to issue and propagate instructions to said collection agent.
30. The method of claim 29, further comprising the step of:
- managing and propagating access control individual repositories with said EDMS.
31. The method of claim 30, further comprising the step of:
- allocating any of a case, collection plan, and individual collection logs to individual evidence repositories.
32. The method of claim 30, further comprising the step of:
- using dedicated repositories for collections from custodians and data sources that reside in jurisdictions having high levels of restriction on cross-border data transfers.
33. The method of claim 30, further comprising the step of:
- using dedicated repositories with increased security for confidential cases or cases having sensitive data.
34. The method of claim 30, further comprising the step of:
- said EDMS issuing collection instructions that include location of a staging area directory that is specific to a selected evidence repository.
35. The method of claim 30, further comprising the step of:
- said EDMS providing legal users with visibility into an overall collection process.
36. The method of claim 35, further comprising the step of:
- notifying said EDMS when exceptions occur in staging area directories, and periodically providing a summary of a data deposition process.
37. The method of claim 35, further comprising the step of:
- notifying said EDMS when exceptions occur during data ingestion and in said evidence repository, and providing a summary said data ingestion process.
38. The method of claim 35, further comprising the step of:
- notifying said EDMS when exceptions occur in data processing tools, and providing a summary of data indexing or processing.
39. A computer readable medium for storing program instructions that, when executed by a processor, cause the processor to implement a method for storing and accessing collected artifacts in an electronic discovery system (EDMS), comprising the steps of:
- providing an evidence repository for managing collected artifacts along with contextual data and metadata;
- providing a collection agent configured to perform artifact collection and to deposit collected artifacts to said repository; and
- providing an EDMS configured to manage electronic discovery workflow in an enterprise and to issue and propagate instructions to said collection agent.
40. An apparatus for storing and accessing collected artifacts in an electronic discovery system (EDMS), comprising:
- an evidence repository for managing collected artifacts along with contextual data and metadata;
- a collection agent configured to perform artifact collection and to deposit collected artifacts to said repository; and
- an EDMS configured to manage electronic discovery workflow in an enterprise and to issue and propagate instructions to said collection agent.
Type: Application
Filed: Jun 29, 2010
Publication Date: Dec 29, 2011
Patent Grant number: 8832148
Inventors: Roman Kisin (San Jose, CA), Pierre Raynaud-Richard (Redwood City, CA)
Application Number: 12/826,471
International Classification: G06F 17/30 (20060101);